Users of information systems, such as the web, often require the ability to find information that they have previously found. One solution to this which has been implemented in web browsing applications is the ability to store a list of favourites (also referred to as bookmarks), which have a title and link to a particular web page. This enables a user to revisit a previously visited and bookmarked web page. However, users may collate large numbers of favourites, and although these may be arranged in a folder structure, it may still be difficult to navigate through. Another solution to aid retrieval of web pages (or other objects) that a user has previously visited is to enable the user to apply one or more tags (or keywords) to the web page along with a location reference to that object. These tags may subsequently be searched in any combination and this provides a more flexible way for a user to find previously visited material.
In order to improve the ability to retrieve web pages that a user has not previously tagged, but may be related to one that a user has tagged, some web sites have incorporated collaborative tagging. This technique enables a user to search for a web page (or other object) based on the tags applied to that object by other users of the same system. In order for such collaborative systems to be effective, the tags applied to an object should be prioritized (or ranked) according to their relative relevance/applicability to the particular object. However, it may require a large number of tagging events before the system reaches a state where the top n ranked tags are stable (i.e. they do not keep churning).
In order to improve the ranking of the tags and the time taken for the identified tags to converge on a prioritized list which is a true representation of each tags true popularity rank with respect to an object, some systems which use collaborative tagging also offer suggestions to a user when attempting to apply a tag to a web page. These suggestions may be based on the tags already applied to the same object by other users of the system. A known method of selecting tags to be suggested to a user is referred to as ‘Top Popular’ which selects a fixed number of the current most popular tags (i.e. those tags most often used by users) for a particular web page (e.g. the six most commonly used tags for a web page may be presented to a user as the suggested tags for the web page). However, problems arise where a user idly selects one or more of the suggested tags without application of their own judgment (this is referred to herein as ‘user imitation’). This can distort the ranking of tags and lead to the ranking converging very slowly on a true representation of each tags true popularity rank, or in some circumstances the ranking may not converge at all.